A comprehensive map of human metabolism has been produced by a large consortium including researchers from EMBL-EBI. Published in Nature Biotechnology, the model is freely available through EMBL-EBI’s BioModels Database. It contains verified information on thousands of metabolites and reactions and represents a goldmine for systems biologists.
Although many human diseases are due to metabolic defects, understanding the endless complexity of human metabolism is a major challenge. Having a complete, ‘gold-standard’ metabolic model will be a major milestone in systems biology because it will make it possible to use computers to test what happens in a human cell. This resource is a major step towards achieving that goal.
Led by the University of Manchester in the UK and the University of San Diego in the US, the researchers adopted a crowd-sourcing approach to map 65 different human cell types and half of the 2,600 enzymes that are known drug targets in order to produce the network model. EMBL-EBI researchers, led by Nicolas Le Novère (now at the Babraham Institute in Cambridge, UK), developed the data infrastructure and the common language the scientists needed to link model and related information. The EMBL-EBI team helped build the model and distribute it through the EMBL-EBI BioModels Database.
Co-author Douglas Kell, Chief Executive of Biotechnology and Biological Sciences Research Council (BBSRC) and Professor of Bioanalytical Science at the Manchester Institute of Biotechnology, says: "To understand the behaviour of a system one must have a model of it. By converting our biological knowledge into a mathematical model format, this work provides a freely accessible tool that will offer an in-depth understanding of human metabolism and its key role in many major human diseases."
Nicolas Le Novère says: “This is a model that links the smallest molecular scale to the full cellular level. It contains more than 8,000 molecular species and 7,000 chemical reactions – no single researcher could have built this alone. Having large collaborations like these, using open standards and data-sharing resources, is crucial for systems biology.”
The metabolic model is available in EMBL-EBI’s BioModels Database in many different formats (www.ebi.ac.uk/biomodels; MODEL1109130000). It contains thousands of cross-references to ChEBI (the chemical dictionary and ontology) and to UniProt (the Universal Protein Resource).
Thiele, I., et al. (2013) A community-driven global reconstruction of human metabolism. Nature Biotechnology (in press); doi: 10.1038/nbt.2488